Risk assessment of the spanish national railway system

Mateos Caballero, Alfonso ORCID: https://orcid.org/0000-0003-4764-6047, Jiménez Martín, Antonio ORCID: https://orcid.org/0000-0002-4947-8430 and Pichardo, Héctor J. (2012). Risk assessment of the spanish national railway system. En: "10th International FLINS Conference. Uncertainty Modeling in Knowledge Engineering and Decision Making", 26/08/2012 - 29/08/2012, Estambul, Turquía.. ISBN 978-981-4417-73-0. pp. 1099-1104.

Descripción

Título: Risk assessment of the spanish national railway system
Autor/es:
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 10th International FLINS Conference. Uncertainty Modeling in Knowledge Engineering and Decision Making
Fechas del Evento: 26/08/2012 - 29/08/2012
Lugar del Evento: Estambul, Turquía.
Título del Libro: Uncertainty Modelling in Knowledge Engineering and Decision Making
Fecha: 2012
ISBN: 978-981-4417-73-0
Materias:
ODS:
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The principal risks in the railway industry are mainly associated with collisions, derailments and level crossing accidents. An understanding of the nature of previous accidents on the railway network is required to identify potential causes and develop safety systems and deploy safety procedures. Risk assessment is a process for determining the risk magnitude to assist with decision-making. We propose a three-step methodology to predict the mean number of fatalities in railway accidents. The first is to predict the mean number of accidents by analyzing generalized linear models and selecting the one that best fits to the available historical data on the basis of goodness-offit statistics. The second is to compute the mean number of fatalities per accident and the third is to estimate the mean number of fatalities. The methodology is illustrated on the Spanish railway system. Statistical models accounting for annual and grouped data for the 1992-2009 time period have been analyzed. After identifying the models for broad and narrow gauges, we predicted mean number of accidents and the number of fatalities for the 2010-18 time period.

Más información

ID de Registro: 19807
Identificador DC: https://oa.upm.es/19807/
Identificador OAI: oai:oa.upm.es:19807
Depositado por: Memoria Investigacion
Depositado el: 17 Oct 2013 15:39
Ultima Modificación: 21 Abr 2016 21:20